Objective:To evaluate the diagnostic performance of resting echocardiography in detecting severe coronary artery stenosis.Methods:A total of 136 patients with suspected coronary artery disease（CAD）who presented to Sichuan Provincial People's Hospital between January 2021 and December 2024 were prospectively enrolled. All patients underwent both coronary computed tomography angiography（CCTA）and transthoracic echocardiography within one week. Based on CCTA results，the patients were divided into non-severe stenosis group（ n=78）and severe stenosis group（ n=58）. Echocardiographic parameters including left atrial maximum volume（LAVmax），left ventricular global longitudinal strain（GLS），left ventricular longitudinal strain of endo-myocardium，mid-myocardium，epi-myocardium（LSendo，LSmid，LSepi），early diastolic mitral inflow velocity（E），early diastolic mitral annular velocity of the lateral and septal walls（e'），and E/e' were measured. Predictive factors for severe coronary stenosis were identified using LASSO regression，and a nomogram model was developed via multivariate Logistic regression. Model performance was evaluated using ROC curves，calibration curves，and decision curve analysis. Results:Multivariate Logistic regression analysis revealed LSendo，LAVmax，and E/e' as independent predictors of severe coronary artery stenosis. The nomogram constructed based on these predictors achieved an area under the curve of 0.798（95% CI=0.723-0.873），with sensitivity and specificity of 0.756 and 0.759，respectively. Conclusions:The resting echocardiography-based nomogram model demonstrates good diagnostic efficacy for severe coronary artery stenosis. It may serve as a noninvasive tool to assist in risk stratification and clinical decision-making in patients with suspected CAD.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

Objective:To evaluate the diagnostic performance of resting echocardiography in detecting severe coronary artery stenosis.Methods:A total of 136 patients with suspected coronary artery disease（CAD）who presented to Sichuan Provincial People's Hospital between January 2021 and December 2024 were prospectively enrolled. All patients underwent both coronary computed tomography angiography（CCTA）and transthoracic echocardiography within one week. Based on CCTA results，the patients were divided into non-severe stenosis group（ n=78）and severe stenosis group（ n=58）. Echocardiographic parameters including left atrial maximum volume（LAVmax），left ventricular global longitudinal strain（GLS），left ventricular longitudinal strain of endo-myocardium，mid-myocardium，epi-myocardium（LSendo，LSmid，LSepi），early diastolic mitral inflow velocity（E），early diastolic mitral annular velocity of the lateral and septal walls（e'），and E/e' were measured. Predictive factors for severe coronary stenosis were identified using LASSO regression，and a nomogram model was developed via multivariate Logistic regression. Model performance was evaluated using ROC curves，calibration curves，and decision curve analysis. Results:Multivariate Logistic regression analysis revealed LSendo，LAVmax，and E/e' as independent predictors of severe coronary artery stenosis. The nomogram constructed based on these predictors achieved an area under the curve of 0.798（95% CI=0.723-0.873），with sensitivity and specificity of 0.756 and 0.759，respectively. Conclusions:The resting echocardiography-based nomogram model demonstrates good diagnostic efficacy for severe coronary artery stenosis. It may serve as a noninvasive tool to assist in risk stratification and clinical decision-making in patients with suspected CAD.

ObjectiveTo investigate the inhibitory effect of Mahuang Xixin Fuzitang on the migration of dendritic cells （DCs） in mice and its underlying mechanism. MethodMouse bone marrow-derived DCs were isolated and cultured. The morphological changes of the cells at different stages were observed under a microscope， and the CD11c⁺ proportion was detected by flow cytometry to identify DC purity. Cells were treated with Mahuang Xixin Fuzitang （1， 2， 5， 10， 20， 40， 50， 100 g·L^-1） for 24 hours， and the effect of Mahuang Xixin Fuzitang on cell proliferation was assessed using the cell counting kit-8 （CCK-8） assay to determine the appropriate concentrations for treatment. After modeling by lipopolysaccharide （LPS） induction， DCs were divided into a blank group， a model group， and Mahuang Xixin Fuzitang groups （2， 4， 8 g·L^-1）. The expression of surface molecules CD80， CD86， and major histocompatibility complex-Ⅱ （MHC-Ⅱ） were detected by flow cytometry. Transwell chamber assay was used to observe cell migration. The levels of chemokine C-C-primitive receptor 7 （CCR7） and chemokine C-X-C-primitive receptor 4 （CXCR4） on the cell surface were detected by enzyme-linked immunosorbent assay （ELISA）. The expression of filamentous actin （F-actin） in the cell microfilament cytoskeleton was detected by immunofluorescence （IF） staining. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to determine the mRNA expression levels of Ras homolog family member A （RhoA） and Rho-associated coiled-coil containing protein kinase 1 （ROCK1）. Western blot analysis was performed to detect the protein expression of RhoA and ROCK1. ResultCompared with the blank group， the model group exhibited significantly higher expression levels of CD80， CD86， and MHC-Ⅱ （P<0.01）， a significantly increased number of cells migrating to the lower chamber （P<0.01）， and significantly elevated levels of CCR7 and CXCR4 （P<0.05， P<0.01）. Additionally， F-actin expression was significantly increased （P<0.01）， and both RhoA and ROCK1 mRNA and protein expression levels were significantly higher （P<0.05， P<0.01）. Compared with the model group， treatment with Mahuang Xixin Fuzitang （2， 4， 8 g·L^-1） for 24 hours resulted in significantly lower expression levels of CD80， CD86， and MHC-Ⅱ （P<0.01）， a significantly reduced number of cells migrating to the lower chamber （P<0.05）， and significantly decreased levels of CCR7 and CXCR4 （P<0.05， P<0.01）. Furthermore， F-actin expression was significantly reduced （P<0.01）， and both RhoA and ROCK1 mRNA and protein expression levels were significantly decreased （P<0.05， P<0.01）. ConclusionMahuang Xixin Fuzitang can inhibit the migration of DCs in mice， and its mechanism of action may be related to reducing the activity of the Rho/ROCK signaling pathway， thereby affecting changes in the cell cytoskeleton.

Objective:To compare the efficacy and safety of venetoclax (VEN) combined with azacitidine (AZA) versus CAG regimen combined with decitabine (DAC) in elderly patients with relapsed acute myeloid leukemia (AML).Methods:From January 2018 to August 2020, the clinical data of forty-five elderly patients with relapse AML at the First Affiliated Hospital of Soochow University were retrospectively analyzed, including 31 males and 14 females. The median age was 66 (60-80) years old. Eighteen patients were administrated with VEN and AZA, while the other 27 were in CAG with DAC. The complete remission (CR) rate, partial remission (PR) rate, total remission rate (ORR), adverse events and overall survival (OS) were compared between the two groups.Results:At the end of the treatment, the ORR in VEN with AZA group was 77.8% (14/18); including 11 CR and 3 PR. In CAG with DAC group, the ORR was 37.0% (10/27); including 8 CR and 2 PR ( P=0.007). Subgroup analysis suggested that VEN with AZA had a higher ORR in patients stratified as intermediate and poor-risk ( P=0.013) or with DNA methylation mutations ( P=0.007). Main adverse events in both groups were bone marrow suppression, infections, nausea and vomiting, anorexia and fatigue. Grade Ⅲ-Ⅳ cytopenia developed in lower incidence of VEN with AZA group, such as leukopenia (66.7% vs. 100%, P=0.002), anemia (50.0% vs. 92.6%, P=0.002), thrombocytopenia (72.2% vs. 96.3%, P=0.031) and neutropenia (61.1% vs. 92.6%, P=0.014). In addition, less grade Ⅲ-Ⅳ infections occurred in VEN with AZA group (66.7% vs. 33.3%, P=0.028), as well as grade Ⅲ-Ⅳ gastrointestinal events (40.7% vs. 11.1%, P=0.032), grade Ⅲ-Ⅳ fatigue (55.6% vs.11.1%, P=0.003) compared with CAG with DAC group. The 1-year OS in VEN with AZA group versus CAG with DAC group was 42.9% and 31.6% respectively ( P=0.150). Conclusion:VEN combined with AZA proves favorable efficacy and tolerablity in elderly patients with relapsed AML.

Neural oscillation is rhythmic or repetitive neural activity in the central nervous system that is usually generated by oscillatory activity of neuronal ensembles, reflecting regular and synchronized activities within these cell populations. According to several oscillatory bands covering frequencies from approximately 0.5 Hz to >100 Hz, neural oscillations are usually classified as delta oscillation (0.5-3 Hz), theta oscillation (4-12 Hz), beta oscillation (12-30 Hz), gamma oscillation (30-100 Hz) and sharp-wave ripples (>100 Hz ripples superimposed on 0.01-3 Hz sharp waves). Neural oscillation in different frequencies can be detected in different brain regions of human and animal during perception, motion and sleep, and plays an essential role in cognition, learning and memory process. In this review, we summarize recent findings on neural oscillations in hippocampus, as well as the mechanism and function of hippocampal theta oscillation, gamma oscillation and sharp-wave ripples. This review may yield new insights into the functions of neural oscillation in general.

Near infrared chemical imaging (NIR-CI) is an emerging technology for rapidly analyzing the critical quality attribute of Chinese materia medica (CMM). It integrates NIR spectroscopy with chemical imaging. In this paper, it provided a systematic introduction to NIR-CI, such as the core part of instrument, the reliability, transformation, analysis and application of high-dimensional data acquisition. In addition, current studies of NIR-CI application in pharmaceutical field were analyzed. Finally, future opportunities and challenges of NIR -CI applications in the quality control of CMM preparation were prospected.

This study was aimed to optimize the near infrared (NIR) variable selection method based on multivariate detection limit (MDL). Using Qing-Kai-Ling (QKL) injection as object, three variable selection methods (interval par-tial least-squares, iPLS; backward interval partial least squares, BiPLS; moving window interval partial least squares, mwPLS) were used to establish the PLS models of baicalin in QKL injection, respectively. The prediction ability of different variable selection method was compared. MDL of all models were calculated in contrast to the MDL value of full spectra PLS model, to select optimal variable selection method. The results showed that different variable selec-tion methods had different prediction ability. Among them, iPLS had the best performance which determination coef-ficient of prediction (Rpre2) and the root mean square errors of prediction (SEP) were 0.996 5 and 602.3 μg·mL-1, re-spectively. All MDLs of different variable selection methods were reduced compared with the full spectra PLS model. The value of iPLS was the lowest comes to be 1.19 μg·mL-1. The results above indicated that the best variable se-lection method for baicalin in QKL injection was iPLS. MDL theory took the error of calibration and validation set and the leverage of external sample into account, which can comprehensively evaluate model detection performance compared to the classic chemical indicator parameters. This method was particularly suitable for the variable selec-tion method optimization of NIR quantitative model of low concentration sample such as Chinese herbal medicine.

Objective To identify significantly differentially expression of rat by genes chip,try to find out the initiating factors and molecular mechanisms that oxidative stress originate or strengthen the steriod-induced necrosis of femoral head(SINFH).Methods Twenty Wistar rats were dived into experimental group and control group randomly.The rats were injected intraperitoneally whith endotoxin,and then injected intramuscularly with high-dose methylprednisolone or saline in experimental group and control group respectively.The mRNA was extracted from the femoral head of rats inevery group,and the cDNA probes were obtained by inverse transcript,and then carried out microarray detection.The quantitative RT-PCR was used to confirm the results of the microarray.Results Histopathological findings revealed that the experimental group rats had femoral head necrosis,trabecular bone disorders,thinning,bone cell necrosis,and the rate of empty lacunae increased,and in control group no femoral head osteonecrosis was found.Total of 27 differentially expressed genes were found,and of which 4 genes(COX6A2,COX4I2,SOD3,and DUSP1)were significantly different.The expression of these 4 genes were down-regulated.The functions of these four genes involved in inhibition of reactive oxygen species(ROS)generation,accelerated removal of ROS and protection tissue from oxidative damage and so on.Conclusion The expression of oxidative stress-related genes in SINFH of rats exist change.COX6A2,COX4I2,SOD3,and DUSP1 are key genes in process of oxidative stress originate or strengthen the SINFH.